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January 25, 2026ProcessesOpen Access

A Novel Predictive Model for Drilling Fluid Rheological Parameters Across Wide Temperature–Pressure Ranges Using Symbolic Regression Algorithm

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Authors

WCWang ChenChina University of Petroleum, BeijingJLJun LiChina University of Petroleum, BeijingHYHongwei YangChina University of Petroleum, Beijing

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Implication

Systematic experiments unveil a predictive model for drilling fluid parameters, enhancing applications in ultra-deep wells.

Key Points

  • The aim is to develop a predictive model for drilling fluid rheological parameters under high-temperature and high-pressure conditions.
  • Conducted systematic rheological experiments on various drilling fluid systems.
  • Tested over wide temperature-pressure ranges from 20–200 °C and 0.1–200 MPa.
  • Developed a unified predictive model using a symbolic regression algorithm.
  • Evaluated model performance against standard statistical metrics and conventional models.
  • The model shows stronger applicability for predicting rheological parameters across broader temperature-pressure ranges.
  • Achieved improved accuracy and robustness for high- and low-density drilling fluids.
  • Overall prediction errors were around 10%, indicating reliability.
  • Effectively overcomes limitations of existing models under specific HTHP conditions.

Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/6975b32bfeba4585c2d6ea26https://doi.org/10.3390/pr14020386
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  1. 1Experimental Study and Rheological Modeling of Water-Based and Oil-Based Drilling Fluids Under Extreme Temperature–Pressure Condition2025 · 10 citations
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  4. 4Prediction of Herschel–Bulkley Parameters for Water-Based Drilling Fluids Under Wide Temperature and Pressure Conditions Using Ambient-Condition Parameters2026 · 1 citations
  5. 5A Machine Learning Model for HTHP Shear-Stress Prediction of Oil-Based Drilling Fluid Using Polynomial-Corrected RBF-CRM2026